§1.1 Field of the Invention
The present invention concerns wireless communications. In particular, the present invention concerns cooperative wireless communications used to improve data throughput, reliability, and/or range.
§1.2 Background Information
Multiple antenna wireless communication systems have been shown to provide much better performance, in terms of error probability and data rate, than single antenna systems. By employing multiple antennas at transmitters and receivers, a Multiple-Input Multiple-Output (“MIMO”) communications system significantly increases the data throughput, reliability and link range without additional bandwidth or transmission power. This is achieved by allowing either transmitting independent data streams on all antennas (spatial multiplexing) or transmitting coded and correlated signals on its antennas (diversity). (See, e.g., L. Zheng and D. N. C. Tse, “Diversity and Multiplexing: A Fundamental Tradeoff In Multiple-Antenna Channels,” IEEE Trans. on Info. Theory, Vol. 49, No. 5, pp. 1073-1096 (October 2003) (incorporated herein by reference).) As the number of antennas increases, so does performance.
Bell Labs Layered Space-Time (See G. J. Foschini, “Layered Space-Time Architecture for Wireless Communication In a Fading Environment When Using Multi-Element Antennas,” AT &T Bell Lab. Tech. J., pp. 41-59 (October 1996) (incorporated herein by reference and referred to as “BLAST”).) is a MIMO communications technique that can achieve a much higher data rate than legacy single antenna systems.
The spacing between the individual antenna elements must be large enough so that uncorrelated spatial fading can be observed at different antennas. Unfortunately, however, due to the limited size of the portable devices, there is a practical limitation on the number of antennas integrated on portable devices. This limits the possible gains for existing MIMO systems.
Cooperative wireless communication refers to active nodes in a wireless network assisting another node in information delivery, with the objective of gaining greater reliability and/or efficiency than the nodes could otherwise obtain individually. Although the wireless medium allows nodes to overhear other transmissions, traditional wireless networks ignore this overheard information (and may consider it to be unwanted interference). On the other hand, cooperative wireless communications networks exploit the broadcast nature of the wireless medium by finding effective ways of pooling the “overheard” information. The idea of tapping into the broadcast nature of wireless medium as a resource to produce more reliable links dates back to the 1970's. Practical cooperative communications concepts (sometimes referred to as “virtual MIMO”), and applications to wireless networks emerged in the last decade, stemming from the tremendous progress made in the previous decade on the design of coding and transmitting schemes for multiple input-multiple output (MIMO) systems.
Recently, several methods have been proposed for cooperation among relay devices (which may be referred to simply as “relays”) to provide spatial diversity gains without utilizing multiple transmitting antennas. (See, e.g., the references: A. Sendonaris, E. Erkip, and B. Aazhang, “User Cooperation Diversity. Part 1: System Description; Part 2: Implementation Aspects and Performance Analysis,” IEEE Trans. Commun., Vol. 51, No. 11, pp. 1927-1948 (November 2003) (incorporated herein by reference); J. N. Laneman, D. N. C. Tse, and G. W. Wornell, “Cooperative Diversity In Wireless Networks: Efficient Protocols and Outage Behavior,” IEEE Trans. Inf. Theory, Vol. 50, No. 12, pp. 3062-3080 (December 2004) (incorporated herein by reference); J. N. Laneman and G. W. Wornell, “Distributed Space-Time-Coded Protocols for Exploiting Cooperative Diversity in Wireless Networks,” IEEE Trans. Inf. Theory, Vol. 49, No. 10, pp. 2415-2525 (October 2003) (incorporated herein by reference); and P. A. Anghel, G. Leus, and M. Kaveh, “Distributed Space-Time Cooperative Systems with Regenerative Relays,” IEEE Trans. Wireless Commun., Vol. 5, No. 11, pp. 3130-3141 (November 2006) (incorporated herein by reference).) The decode-and-forward strategy is one such method that has been shown to provide various benefits in addition to being information-theoretically optimal in certain scenarios. Common to all decode-and-forward strategies is the fact that the relays first decode the source message reliably and then relay it after re-encoding.
However, if the BLAST structure is applied directly to the distributed cooperation system, where each individual distributed antenna transmits the same waveform of an antenna as in the real MIMO BLAST system, the following challenges must be overcome with current systems.
First, currently, each relay participating in a distributed BLAST needs to be numbered, so that it knows exactly which antenna it will mimic in the underlying BLAST. Hence the exact set of participating relays needs to be determined and distributed to the nodes of the network. Such information may be distributed using separate signaling packets or piggy-backed in the data packet from the source. Unfortunately, network changes (e.g., due to a relay entering or leaving the system, or the loss or degradation of a channel between relay and a source or destination) need to be signaled, and distributing the foregoing information could become impractical.
Second, for relay selection, a detailed global knowledge of the channel conditions between each potential relay and the destination might be required for the system to be practical. To disseminate this information to the source nodes, special signaling at the MAC layer might be needed. Mobility, channel fading and the large number of nodes in a typical wireless network make it very costly, if not impossible, to distribute such information with minimal overhead within the channel coherence time (that is, the time period over which the signal strength information is valid).
Third, if information on global channel conditions is not available, relay selection and code allocation has to be based on information that is likely outdated. However due to variations in the channel, the pre-determined error rate thresholds at the chosen relays may not be met resulting in severe loss in performance.
Fourth, even though nodes other than the chosen relays may decode the source information correctly, they are not allowed to transmit (since a specific channel is transmitted to a specific, assigned, relay). This sacrifices the diversity and coding gains of BLAST.
Fifth, a distributed BLAST system would have tight constraints on the time synchronization of the nodes, putting a very heavy (if not unrealistic) burden on the MAC (layer 2—data link) and PHY (layer 1—physical) layers.
Sixth, each individual wireless link is not necessarily reliable. In a distributed BLAST system, even if only one of the relays fails to receive the data sent from the source device, one stream of the data is lost, and the destination receiver would be unable to decode the packet. Similarly, system performance is bounded by the worst link from the relays to the destination.
Thus, it would be useful to overcome, or better yet avoid, the foregoing problems and challenges associated with a distributed BLAST system, while enjoying the benefits of spatial diversity gains.